Overview

Dataset statistics

Number of variables15
Number of observations940
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory110.3 KiB
Average record size in memory120.1 B

Variable types

Numeric14
Categorical1

Alerts

TotalSteps is highly overall correlated with TotalDistance and 8 other fieldsHigh correlation
TotalDistance is highly overall correlated with TotalSteps and 8 other fieldsHigh correlation
TrackerDistance is highly overall correlated with TotalSteps and 8 other fieldsHigh correlation
VeryActiveDistance is highly overall correlated with TotalSteps and 5 other fieldsHigh correlation
ModeratelyActiveDistance is highly overall correlated with TotalSteps and 5 other fieldsHigh correlation
LightActiveDistance is highly overall correlated with TotalSteps and 3 other fieldsHigh correlation
VeryActiveMinutes is highly overall correlated with TotalSteps and 6 other fieldsHigh correlation
FairlyActiveMinutes is highly overall correlated with TotalSteps and 5 other fieldsHigh correlation
LightlyActiveMinutes is highly overall correlated with TotalSteps and 3 other fieldsHigh correlation
Calories is highly overall correlated with TotalSteps and 3 other fieldsHigh correlation
ActivityDate is uniformly distributedUniform
TotalSteps has 77 (8.2%) zerosZeros
TotalDistance has 78 (8.3%) zerosZeros
TrackerDistance has 78 (8.3%) zerosZeros
LoggedActivitiesDistance has 908 (96.6%) zerosZeros
VeryActiveDistance has 413 (43.9%) zerosZeros
ModeratelyActiveDistance has 386 (41.1%) zerosZeros
LightActiveDistance has 85 (9.0%) zerosZeros
SedentaryActiveDistance has 858 (91.3%) zerosZeros
VeryActiveMinutes has 409 (43.5%) zerosZeros
FairlyActiveMinutes has 384 (40.9%) zerosZeros
LightlyActiveMinutes has 84 (8.9%) zerosZeros

Reproduction

Analysis started2023-01-14 18:32:57.427692
Analysis finished2023-01-14 18:33:11.994926
Duration14.57 seconds
Software versionpandas-profiling vv3.6.2
Download configurationconfig.json

Variables

Id
Real number (ℝ)

Distinct33
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8554074 × 109
Minimum1.5039604 × 109
Maximum8.8776894 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2023-01-14T10:33:12.047478image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1.5039604 × 109
5-th percentile1.6245801 × 109
Q12.320127 × 109
median4.445115 × 109
Q36.9621811 × 109
95-th percentile8.7920097 × 109
Maximum8.8776894 × 109
Range7.373729 × 109
Interquartile range (IQR)4.6420541 × 109

Descriptive statistics

Standard deviation2.4248055 × 109
Coefficient of variation (CV)0.4994031
Kurtosis-1.2730307
Mean4.8554074 × 109
Median Absolute Deviation (MAD)2.418763 × 109
Skewness0.1771249
Sum4.5640829 × 1012
Variance5.8796816 × 1018
MonotonicityIncreasing
2023-01-14T10:33:12.115329image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1503960366 31
 
3.3%
4319703577 31
 
3.3%
8583815059 31
 
3.3%
8378563200 31
 
3.3%
8053475328 31
 
3.3%
7086361926 31
 
3.3%
6962181067 31
 
3.3%
5553957443 31
 
3.3%
4702921684 31
 
3.3%
4558609924 31
 
3.3%
Other values (23) 630
67.0%
ValueCountFrequency (%)
1503960366 31
3.3%
1624580081 31
3.3%
1644430081 30
3.2%
1844505072 31
3.3%
1927972279 31
3.3%
2022484408 31
3.3%
2026352035 31
3.3%
2320127002 31
3.3%
2347167796 18
1.9%
2873212765 31
3.3%
ValueCountFrequency (%)
8877689391 31
3.3%
8792009665 29
3.1%
8583815059 31
3.3%
8378563200 31
3.3%
8253242879 19
2.0%
8053475328 31
3.3%
7086361926 31
3.3%
7007744171 26
2.8%
6962181067 31
3.3%
6775888955 26
2.8%

ActivityDate
Categorical

Distinct31
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
4/12/2016
 
33
4/14/2016
 
33
4/15/2016
 
33
4/13/2016
 
33
4/23/2016
 
32
Other values (26)
776 

Length

Max length9
Median length9
Mean length8.7255319
Min length8

Characters and Unicode

Total characters8202
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4/12/2016
2nd row4/13/2016
3rd row4/14/2016
4th row4/15/2016
5th row4/16/2016

Common Values

ValueCountFrequency (%)
4/12/2016 33
 
3.5%
4/14/2016 33
 
3.5%
4/15/2016 33
 
3.5%
4/13/2016 33
 
3.5%
4/23/2016 32
 
3.4%
4/29/2016 32
 
3.4%
4/28/2016 32
 
3.4%
4/26/2016 32
 
3.4%
4/25/2016 32
 
3.4%
4/24/2016 32
 
3.4%
Other values (21) 616
65.5%

Length

2023-01-14T10:33:12.179965image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
4/12/2016 33
 
3.5%
4/15/2016 33
 
3.5%
4/13/2016 33
 
3.5%
4/14/2016 33
 
3.5%
4/22/2016 32
 
3.4%
4/21/2016 32
 
3.4%
4/16/2016 32
 
3.4%
4/18/2016 32
 
3.4%
4/19/2016 32
 
3.4%
4/20/2016 32
 
3.4%
Other values (21) 616
65.5%

Most occurring characters

ValueCountFrequency (%)
/ 1880
22.9%
2 1375
16.8%
1 1357
16.5%
6 1033
12.6%
0 1029
12.5%
4 705
 
8.6%
5 423
 
5.2%
3 125
 
1.5%
7 93
 
1.1%
9 91
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6322
77.1%
Other Punctuation 1880
 
22.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1375
21.7%
1 1357
21.5%
6 1033
16.3%
0 1029
16.3%
4 705
11.2%
5 423
 
6.7%
3 125
 
2.0%
7 93
 
1.5%
9 91
 
1.4%
8 91
 
1.4%
Other Punctuation
ValueCountFrequency (%)
/ 1880
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8202
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 1880
22.9%
2 1375
16.8%
1 1357
16.5%
6 1033
12.6%
0 1029
12.5%
4 705
 
8.6%
5 423
 
5.2%
3 125
 
1.5%
7 93
 
1.1%
9 91
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8202
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 1880
22.9%
2 1375
16.8%
1 1357
16.5%
6 1033
12.6%
0 1029
12.5%
4 705
 
8.6%
5 423
 
5.2%
3 125
 
1.5%
7 93
 
1.1%
9 91
 
1.1%

TotalSteps
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct842
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7637.9106
Minimum0
Maximum36019
Zeros77
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2023-01-14T10:33:12.244638image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13789.75
median7405.5
Q310727
95-th percentile15485.1
Maximum36019
Range36019
Interquartile range (IQR)6937.25

Descriptive statistics

Standard deviation5087.1507
Coefficient of variation (CV)0.66603957
Kurtosis1.1691112
Mean7637.9106
Median Absolute Deviation (MAD)3446.5
Skewness0.65289494
Sum7179636
Variance25879103
MonotonicityNot monotonic
2023-01-14T10:33:12.316156image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 77
 
8.2%
244 2
 
0.2%
6708 2
 
0.2%
9167 2
 
0.2%
6175 2
 
0.2%
10538 2
 
0.2%
1510 2
 
0.2%
8538 2
 
0.2%
7937 2
 
0.2%
4363 2
 
0.2%
Other values (832) 845
89.9%
ValueCountFrequency (%)
0 77
8.2%
4 1
 
0.1%
8 1
 
0.1%
9 1
 
0.1%
16 1
 
0.1%
17 1
 
0.1%
29 1
 
0.1%
31 1
 
0.1%
42 1
 
0.1%
44 1
 
0.1%
ValueCountFrequency (%)
36019 1
0.1%
29326 1
0.1%
27745 1
0.1%
23629 1
0.1%
23186 1
0.1%
22988 1
0.1%
22770 1
0.1%
22359 1
0.1%
22244 1
0.1%
22026 1
0.1%

TotalDistance
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct615
Distinct (%)65.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4897021
Minimum0
Maximum28.030001
Zeros78
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2023-01-14T10:33:12.391439image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.6199999
median5.2449999
Q37.7125
95-th percentile11.6565
Maximum28.030001
Range28.030001
Interquartile range (IQR)5.0925001

Descriptive statistics

Standard deviation3.9246059
Coefficient of variation (CV)0.71490325
Kurtosis3.1130184
Mean5.4897021
Median Absolute Deviation (MAD)2.5600001
Skewness1.1262736
Sum5160.32
Variance15.402532
MonotonicityNot monotonic
2023-01-14T10:33:12.546300image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 78
 
8.3%
2.599999905 5
 
0.5%
0.009999999776 5
 
0.5%
3.910000086 4
 
0.4%
4.949999809 4
 
0.4%
1.789999962 4
 
0.4%
4.329999924 4
 
0.4%
2.680000067 4
 
0.4%
3.50999999 4
 
0.4%
4.900000095 4
 
0.4%
Other values (605) 824
87.7%
ValueCountFrequency (%)
0 78
8.3%
0.009999999776 5
 
0.5%
0.01999999955 1
 
0.1%
0.02999999933 2
 
0.2%
0.03999999911 1
 
0.1%
0.07999999821 1
 
0.1%
0.09000000358 1
 
0.1%
0.1000000015 1
 
0.1%
0.1099999994 1
 
0.1%
0.1299999952 1
 
0.1%
ValueCountFrequency (%)
28.03000069 1
0.1%
26.71999931 1
0.1%
25.29000092 1
0.1%
20.64999962 1
0.1%
20.39999962 1
0.1%
19.55999947 1
0.1%
19.34000015 1
0.1%
18.97999954 1
0.1%
18.25 1
0.1%
18.11000061 1
0.1%

TrackerDistance
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct613
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4753511
Minimum0
Maximum28.030001
Zeros78
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2023-01-14T10:33:12.618384image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.6199999
median5.2449999
Q37.71
95-th percentile11.6565
Maximum28.030001
Range28.030001
Interquartile range (IQR)5.0900002

Descriptive statistics

Standard deviation3.9072759
Coefficient of variation (CV)0.71361195
Kurtosis3.2038891
Mean5.4753511
Median Absolute Deviation (MAD)2.5550003
Skewness1.1345496
Sum5146.83
Variance15.266805
MonotonicityNot monotonic
2023-01-14T10:33:12.686010image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 78
 
8.3%
2.599999905 5
 
0.5%
0.009999999776 5
 
0.5%
3.910000086 4
 
0.4%
2.680000067 4
 
0.4%
1.789999962 4
 
0.4%
4.329999924 4
 
0.4%
4.949999809 4
 
0.4%
3.50999999 4
 
0.4%
8.739999771 4
 
0.4%
Other values (603) 824
87.7%
ValueCountFrequency (%)
0 78
8.3%
0.009999999776 5
 
0.5%
0.01999999955 1
 
0.1%
0.02999999933 2
 
0.2%
0.03999999911 1
 
0.1%
0.07999999821 1
 
0.1%
0.09000000358 1
 
0.1%
0.1000000015 1
 
0.1%
0.1099999994 1
 
0.1%
0.1299999952 1
 
0.1%
ValueCountFrequency (%)
28.03000069 1
0.1%
26.71999931 1
0.1%
25.29000092 1
0.1%
20.64999962 1
0.1%
20.39999962 1
0.1%
19.55999947 1
0.1%
19.34000015 1
0.1%
18.97999954 1
0.1%
18.25 1
0.1%
18.11000061 1
0.1%

LoggedActivitiesDistance
Real number (ℝ)

Distinct19
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.10817094
Minimum0
Maximum4.942142
Zeros908
Zeros (%)96.6%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2023-01-14T10:33:12.747848image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum4.942142
Range4.942142
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.61989652
Coefficient of variation (CV)5.7307121
Kurtosis41.295941
Mean0.10817094
Median Absolute Deviation (MAD)0
Skewness6.2974404
Sum101.68068
Variance0.38427169
MonotonicityNot monotonic
2023-01-14T10:33:12.802669image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 908
96.6%
2.092147112 9
 
1.0%
2.253081083 7
 
0.7%
4.081692219 1
 
0.1%
4.861792088 1
 
0.1%
4.878232002 1
 
0.1%
4.912367821 1
 
0.1%
2.832325935 1
 
0.1%
4.911146164 1
 
0.1%
4.885604858 1
 
0.1%
Other values (9) 9
 
1.0%
ValueCountFrequency (%)
0 908
96.6%
1.959596038 1
 
0.1%
2.092147112 9
 
1.0%
2.253081083 7
 
0.7%
2.785175085 1
 
0.1%
2.832325935 1
 
0.1%
3.167821884 1
 
0.1%
3.285414934 1
 
0.1%
4.081692219 1
 
0.1%
4.851306915 1
 
0.1%
ValueCountFrequency (%)
4.94214201 1
0.1%
4.930550098 1
0.1%
4.924840927 1
0.1%
4.912367821 1
0.1%
4.911146164 1
0.1%
4.885604858 1
0.1%
4.878232002 1
0.1%
4.869782925 1
0.1%
4.861792088 1
0.1%
4.851306915 1
0.1%

VeryActiveDistance
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct333
Distinct (%)35.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5026809
Minimum0
Maximum21.92
Zeros413
Zeros (%)43.9%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2023-01-14T10:33:12.868412image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.20999999
Q32.0524999
95-th percentile6.4030001
Maximum21.92
Range21.92
Interquartile range (IQR)2.0524999

Descriptive statistics

Standard deviation2.6589412
Coefficient of variation (CV)1.769465
Kurtosis11.910951
Mean1.5026809
Median Absolute Deviation (MAD)0.20999999
Skewness2.99617
Sum1412.52
Variance7.0699681
MonotonicityNot monotonic
2023-01-14T10:33:12.938245image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 413
43.9%
0.0700000003 9
 
1.0%
0.05999999866 6
 
0.6%
0.1400000006 5
 
0.5%
0.3300000131 5
 
0.5%
0.3400000036 4
 
0.4%
1.059999943 4
 
0.4%
0.3600000143 4
 
0.4%
1.00999999 4
 
0.4%
2.789999962 4
 
0.4%
Other values (323) 482
51.3%
ValueCountFrequency (%)
0 413
43.9%
0.01999999955 2
 
0.2%
0.03999999911 1
 
0.1%
0.05000000075 3
 
0.3%
0.05999999866 6
 
0.6%
0.0700000003 9
 
1.0%
0.07999999821 4
 
0.4%
0.09000000358 1
 
0.1%
0.1099999994 3
 
0.3%
0.1199999973 3
 
0.3%
ValueCountFrequency (%)
21.92000008 1
0.1%
21.65999985 1
0.1%
13.39999962 1
0.1%
13.26000023 1
0.1%
13.23999977 1
0.1%
13.22000027 1
0.1%
13.13000011 1
0.1%
13.06999969 1
0.1%
12.78999996 1
0.1%
12.53999996 1
0.1%

ModeratelyActiveDistance
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct211
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.56754255
Minimum0
Maximum6.48
Zeros386
Zeros (%)41.1%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2023-01-14T10:33:13.009330image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.23999999
Q30.80000001
95-th percentile2.1300001
Maximum6.48
Range6.48
Interquartile range (IQR)0.80000001

Descriptive statistics

Standard deviation0.88358032
Coefficient of variation (CV)1.556853
Kurtosis10.125629
Mean0.56754255
Median Absolute Deviation (MAD)0.23999999
Skewness2.7711936
Sum533.49
Variance0.78071418
MonotonicityNot monotonic
2023-01-14T10:33:13.083611image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 386
41.1%
0.200000003 9
 
1.0%
0.2800000012 9
 
1.0%
0.400000006 9
 
1.0%
0.25 8
 
0.9%
0.3100000024 8
 
0.9%
0.9300000072 8
 
0.9%
0.4199999869 8
 
0.9%
0.2700000107 7
 
0.7%
0.5699999928 7
 
0.7%
Other values (201) 481
51.2%
ValueCountFrequency (%)
0 386
41.1%
0.009999999776 1
 
0.1%
0.01999999955 1
 
0.1%
0.02999999933 3
 
0.3%
0.03999999911 3
 
0.3%
0.05000000075 3
 
0.3%
0.05999999866 3
 
0.3%
0.0700000003 2
 
0.2%
0.07999999821 4
 
0.4%
0.09000000358 2
 
0.2%
ValueCountFrequency (%)
6.480000019 1
 
0.1%
6.210000038 1
 
0.1%
5.599999905 1
 
0.1%
5.400000095 1
 
0.1%
5.239999771 1
 
0.1%
5.119999886 1
 
0.1%
4.579999924 1
 
0.1%
4.559999943 1
 
0.1%
4.349999905 1
 
0.1%
4.21999979 3
0.3%

LightActiveDistance
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct491
Distinct (%)52.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3408191
Minimum0
Maximum10.71
Zeros85
Zeros (%)9.0%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2023-01-14T10:33:13.169999image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.945
median3.3649999
Q34.7825001
95-th percentile6.462
Maximum10.71
Range10.71
Interquartile range (IQR)2.8375001

Descriptive statistics

Standard deviation2.0406554
Coefficient of variation (CV)0.61082486
Kurtosis-0.18030027
Mean3.3408191
Median Absolute Deviation (MAD)1.4200002
Skewness0.18224747
Sum3140.37
Variance4.1642744
MonotonicityNot monotonic
2023-01-14T10:33:13.245892image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 85
 
9.0%
4.179999828 6
 
0.6%
3.170000076 6
 
0.6%
4.880000114 6
 
0.6%
3.230000019 6
 
0.6%
3.940000057 5
 
0.5%
3.25999999 5
 
0.5%
0.009999999776 5
 
0.5%
4.460000038 5
 
0.5%
5.409999847 5
 
0.5%
Other values (481) 806
85.7%
ValueCountFrequency (%)
0 85
9.0%
0.009999999776 5
 
0.5%
0.01999999955 1
 
0.1%
0.02999999933 3
 
0.3%
0.03999999911 1
 
0.1%
0.05999999866 1
 
0.1%
0.09000000358 1
 
0.1%
0.1000000015 1
 
0.1%
0.1099999994 1
 
0.1%
0.1299999952 2
 
0.2%
ValueCountFrequency (%)
10.71000004 1
0.1%
10.56999969 1
0.1%
10.30000019 1
0.1%
9.479999542 1
0.1%
9.460000038 1
0.1%
8.970000267 1
0.1%
8.789999962 1
0.1%
8.680000305 1
0.1%
8.409999847 1
0.1%
8.270000458 1
0.1%

SedentaryActiveDistance
Real number (ℝ)

Distinct9
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.001606383
Minimum0
Maximum0.11
Zeros858
Zeros (%)91.3%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2023-01-14T10:33:13.306824image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.0099999998
Maximum0.11
Range0.11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0073461763
Coefficient of variation (CV)4.5731164
Kurtosis99.127446
Mean0.001606383
Median Absolute Deviation (MAD)0
Skewness8.5898992
Sum1.51
Variance5.3966306 × 10-5
MonotonicityNot monotonic
2023-01-14T10:33:13.354896image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 858
91.3%
0.009999999776 50
 
5.3%
0.01999999955 21
 
2.2%
0.02999999933 4
 
0.4%
0.05000000075 3
 
0.3%
0.0700000003 1
 
0.1%
0.03999999911 1
 
0.1%
0.1099999994 1
 
0.1%
0.1000000015 1
 
0.1%
ValueCountFrequency (%)
0 858
91.3%
0.009999999776 50
 
5.3%
0.01999999955 21
 
2.2%
0.02999999933 4
 
0.4%
0.03999999911 1
 
0.1%
0.05000000075 3
 
0.3%
0.0700000003 1
 
0.1%
0.1000000015 1
 
0.1%
0.1099999994 1
 
0.1%
ValueCountFrequency (%)
0.1099999994 1
 
0.1%
0.1000000015 1
 
0.1%
0.0700000003 1
 
0.1%
0.05000000075 3
 
0.3%
0.03999999911 1
 
0.1%
0.02999999933 4
 
0.4%
0.01999999955 21
 
2.2%
0.009999999776 50
 
5.3%
0 858
91.3%

VeryActiveMinutes
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct122
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.164894
Minimum0
Maximum210
Zeros409
Zeros (%)43.5%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2023-01-14T10:33:13.418762image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q332
95-th percentile93.05
Maximum210
Range210
Interquartile range (IQR)32

Descriptive statistics

Standard deviation32.844803
Coefficient of variation (CV)1.551853
Kurtosis5.7780701
Mean21.164894
Median Absolute Deviation (MAD)4
Skewness2.1761432
Sum19895
Variance1078.7811
MonotonicityNot monotonic
2023-01-14T10:33:13.487605image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 409
43.5%
1 23
 
2.4%
2 18
 
1.9%
3 16
 
1.7%
8 15
 
1.6%
6 14
 
1.5%
11 14
 
1.5%
19 13
 
1.4%
5 13
 
1.4%
14 12
 
1.3%
Other values (112) 393
41.8%
ValueCountFrequency (%)
0 409
43.5%
1 23
 
2.4%
2 18
 
1.9%
3 16
 
1.7%
4 10
 
1.1%
5 13
 
1.4%
6 14
 
1.5%
7 11
 
1.2%
8 15
 
1.6%
9 7
 
0.7%
ValueCountFrequency (%)
210 1
0.1%
207 1
0.1%
200 1
0.1%
194 1
0.1%
186 1
0.1%
184 1
0.1%
137 1
0.1%
132 1
0.1%
129 1
0.1%
125 2
0.2%

FairlyActiveMinutes
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct81
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.564894
Minimum0
Maximum143
Zeros384
Zeros (%)40.9%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2023-01-14T10:33:13.558587image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q319
95-th percentile51
Maximum143
Range143
Interquartile range (IQR)19

Descriptive statistics

Standard deviation19.987404
Coefficient of variation (CV)1.4734656
Kurtosis7.9957314
Mean13.564894
Median Absolute Deviation (MAD)6
Skewness2.479492
Sum12751
Variance399.49632
MonotonicityNot monotonic
2023-01-14T10:33:13.629056image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 384
40.9%
8 36
 
3.8%
6 23
 
2.4%
5 23
 
2.4%
16 22
 
2.3%
7 20
 
2.1%
10 19
 
2.0%
9 19
 
2.0%
13 18
 
1.9%
11 18
 
1.9%
Other values (71) 358
38.1%
ValueCountFrequency (%)
0 384
40.9%
1 10
 
1.1%
2 8
 
0.9%
3 9
 
1.0%
4 14
 
1.5%
5 23
 
2.4%
6 23
 
2.4%
7 20
 
2.1%
8 36
 
3.8%
9 19
 
2.0%
ValueCountFrequency (%)
143 1
 
0.1%
125 1
 
0.1%
122 1
 
0.1%
116 1
 
0.1%
115 1
 
0.1%
113 1
 
0.1%
98 1
 
0.1%
96 1
 
0.1%
95 5
0.5%
94 1
 
0.1%

LightlyActiveMinutes
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct335
Distinct (%)35.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192.81277
Minimum0
Maximum518
Zeros84
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2023-01-14T10:33:13.702847image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1127
median199
Q3264
95-th percentile369.05
Maximum518
Range518
Interquartile range (IQR)137

Descriptive statistics

Standard deviation109.1747
Coefficient of variation (CV)0.56622132
Kurtosis-0.36011793
Mean192.81277
Median Absolute Deviation (MAD)69
Skewness-0.037929343
Sum181244
Variance11919.115
MonotonicityNot monotonic
2023-01-14T10:33:13.777244image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 84
 
8.9%
206 12
 
1.3%
258 10
 
1.1%
195 9
 
1.0%
214 8
 
0.9%
139 7
 
0.7%
238 7
 
0.7%
141 7
 
0.7%
199 7
 
0.7%
227 7
 
0.7%
Other values (325) 782
83.2%
ValueCountFrequency (%)
0 84
8.9%
1 3
 
0.3%
2 4
 
0.4%
3 3
 
0.3%
4 1
 
0.1%
9 3
 
0.3%
10 2
 
0.2%
11 1
 
0.1%
12 2
 
0.2%
15 1
 
0.1%
ValueCountFrequency (%)
518 1
0.1%
513 1
0.1%
512 1
0.1%
487 1
0.1%
480 1
0.1%
475 1
0.1%
461 1
0.1%
458 1
0.1%
448 1
0.1%
439 1
0.1%

SedentaryMinutes
Real number (ℝ)

Distinct549
Distinct (%)58.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean991.21064
Minimum0
Maximum1440
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2023-01-14T10:33:13.936714image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile536.7
Q1729.75
median1057.5
Q31229.5
95-th percentile1440
Maximum1440
Range1440
Interquartile range (IQR)499.75

Descriptive statistics

Standard deviation301.26744
Coefficient of variation (CV)0.30393887
Kurtosis-0.66595003
Mean991.21064
Median Absolute Deviation (MAD)261
Skewness-0.29449809
Sum931738
Variance90762.068
MonotonicityNot monotonic
2023-01-14T10:33:14.006352image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1440 79
 
8.4%
1182 7
 
0.7%
692 6
 
0.6%
1112 5
 
0.5%
1131 5
 
0.5%
1122 5
 
0.5%
1105 5
 
0.5%
709 5
 
0.5%
1119 5
 
0.5%
728 5
 
0.5%
Other values (539) 813
86.5%
ValueCountFrequency (%)
0 1
0.1%
2 1
0.1%
13 1
0.1%
48 1
0.1%
111 1
0.1%
125 1
0.1%
127 1
0.1%
218 1
0.1%
222 1
0.1%
241 1
0.1%
ValueCountFrequency (%)
1440 79
8.4%
1439 3
 
0.3%
1438 3
 
0.3%
1437 2
 
0.2%
1431 1
 
0.1%
1430 2
 
0.2%
1428 1
 
0.1%
1423 1
 
0.1%
1420 1
 
0.1%
1413 1
 
0.1%

Calories
Real number (ℝ)

Distinct734
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2303.6096
Minimum0
Maximum4900
Zeros4
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2023-01-14T10:33:14.080551image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1372.85
Q11828.5
median2134
Q32793.25
95-th percentile3654.25
Maximum4900
Range4900
Interquartile range (IQR)964.75

Descriptive statistics

Standard deviation718.16686
Coefficient of variation (CV)0.3117572
Kurtosis0.62502694
Mean2303.6096
Median Absolute Deviation (MAD)467
Skewness0.42245048
Sum2165393
Variance515763.64
MonotonicityNot monotonic
2023-01-14T10:33:14.153399image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1980 13
 
1.4%
2063 11
 
1.2%
1841 9
 
1.0%
1688 9
 
1.0%
1347 8
 
0.9%
2225 4
 
0.4%
1819 4
 
0.4%
2044 4
 
0.4%
1922 4
 
0.4%
0 4
 
0.4%
Other values (724) 870
92.6%
ValueCountFrequency (%)
0 4
0.4%
52 1
 
0.1%
57 1
 
0.1%
120 1
 
0.1%
257 1
 
0.1%
403 1
 
0.1%
665 1
 
0.1%
741 1
 
0.1%
928 1
 
0.1%
1002 1
 
0.1%
ValueCountFrequency (%)
4900 1
0.1%
4552 1
0.1%
4547 1
0.1%
4546 1
0.1%
4501 1
0.1%
4398 1
0.1%
4392 1
0.1%
4274 1
0.1%
4236 1
0.1%
4163 1
0.1%

Interactions

2023-01-14T10:33:10.840097image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:57.874662image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:58.946315image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:59.940711image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:00.954622image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:01.894168image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:02.930953image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:03.849461image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:04.893468image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:05.827258image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:06.868518image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:07.792866image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:08.844256image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:09.778658image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:10.909808image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:57.960071image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:59.019157image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:00.010308image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:01.024951image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:01.964028image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:02.999287image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:03.922127image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:04.962094image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:05.896230image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:06.937828image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:07.862667image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:08.913563image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:09.851578image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:10.978929image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:58.031229image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:59.093893image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:00.079034image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:01.093946image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:02.035180image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:03.067429image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:03.993329image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:05.030929image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:05.968029image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:07.005755image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:07.933414image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:08.982026image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:09.924547image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:11.043584image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:58.101465image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:59.162077image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:00.145729image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:01.160105image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:02.101259image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:03.132530image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:04.059343image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:05.098370image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:06.034258image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:07.070349image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:08.001337image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:09.047531image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:09.992812image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:11.108716image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:58.239220image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:59.231738image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:00.296226image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:01.224718image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:02.169295image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:03.195550image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:04.125834image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:05.164060image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:06.101899image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:07.133775image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:08.070704image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:09.112521image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:10.060113image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:11.173589image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:58.307000image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:59.301502image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:00.361246image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:01.292078image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:02.236072image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:03.259793image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:04.194796image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:05.231553image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:06.170348image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:07.197648image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:08.137962image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:09.179600image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:10.129367image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:11.237255image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:58.374122image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:59.368210image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:00.424508image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:01.355807image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:02.392400image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:03.322353image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:04.260755image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:05.295312image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:06.235772image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:07.263638image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:08.204134image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:09.242316image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:10.196089image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:11.305192image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:58.444685image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:59.438914image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:00.491009image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:01.425497image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:02.462743image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:03.392343image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:04.331639image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:05.363094image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:06.304593image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:07.330095image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:08.273588image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:09.310348image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:10.266114image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:11.369642image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:58.518498image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:59.509759image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:00.557835image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:01.491753image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:02.527320image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:03.457506image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:04.486289image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:05.428253image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:06.372177image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:07.394760image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:08.340912image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:09.376412image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:10.335489image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:11.436403image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:58.596193image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:59.582589image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:00.623636image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:01.558566image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:02.596617image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:03.522106image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:04.554523image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:05.495073image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:06.525846image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:07.462548image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:08.411764image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:09.444269image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:10.405751image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:11.498781image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:58.662508image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:59.650261image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:00.686949image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:01.621121image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:02.661319image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:03.583426image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:04.618751image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:05.558137image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:06.589694image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:07.525131image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:08.564055image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:09.510035image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:10.471670image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:11.569422image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:58.734320image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:59.725871image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:00.756197image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:01.691991image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:02.730883image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:03.650786image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:04.688274image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:05.627673image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:06.664006image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:07.594149image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:08.636398image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:09.578679image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:10.631717image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:11.635317image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:58.804426image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:59.795827image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:00.821520image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:01.759407image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:02.797381image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:03.717622image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:04.756221image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:05.692310image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:06.729922image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:07.659573image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:08.704060image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:09.643665image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:10.700935image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:11.705536image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:58.877636image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:32:59.870267image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:00.890079image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:01.828510image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:02.866558image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:03.786087image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:04.827139image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:05.760672image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:06.800507image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:07.728025image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:08.776566image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:09.713254image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-01-14T10:33:10.771260image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2023-01-14T10:33:14.220207image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
IdTotalStepsTotalDistanceTrackerDistanceLoggedActivitiesDistanceVeryActiveDistanceModeratelyActiveDistanceLightActiveDistanceSedentaryActiveDistanceVeryActiveMinutesFairlyActiveMinutesLightlyActiveMinutesSedentaryMinutesCaloriesActivityDate
Id1.0000.1580.1990.1970.2100.2230.1110.030-0.1140.2510.125-0.084-0.0640.4290.000
TotalSteps0.1581.0000.9920.9920.1800.7700.7040.7150.0150.7490.6890.581-0.4280.5590.000
TotalDistance0.1990.9921.0001.0000.2030.7760.7010.7150.0130.7520.6850.559-0.4140.6170.000
TrackerDistance0.1970.9921.0001.0000.1930.7750.7010.7140.0110.7510.6860.558-0.4150.6170.000
LoggedActivitiesDistance0.2100.1800.2030.1931.0000.2260.1570.1390.0100.2650.1330.057-0.0870.2260.000
VeryActiveDistance0.2230.7700.7760.7750.2261.0000.7490.285-0.0640.9700.7430.158-0.2350.4970.000
ModeratelyActiveDistance0.1110.7040.7010.7010.1570.7491.0000.361-0.0960.7340.9800.244-0.3080.4030.016
LightActiveDistance0.0300.7150.7150.7140.1390.2850.3611.0000.1420.2850.3450.878-0.4660.4650.000
SedentaryActiveDistance-0.1140.0150.0130.0110.010-0.064-0.0960.1421.000-0.057-0.1030.1940.0960.0100.000
VeryActiveMinutes0.2510.7490.7520.7510.2650.9700.7340.285-0.0571.0000.7460.152-0.2410.5400.000
FairlyActiveMinutes0.1250.6890.6850.6860.1330.7430.9800.345-0.1030.7461.0000.232-0.3140.4350.051
LightlyActiveMinutes-0.0840.5810.5590.5580.0570.1580.2440.8780.1940.1520.2321.000-0.4800.2860.000
SedentaryMinutes-0.064-0.428-0.414-0.415-0.087-0.235-0.308-0.4660.096-0.241-0.314-0.4801.000-0.1520.097
Calories0.4290.5590.6170.6170.2260.4970.4030.4650.0100.5400.4350.286-0.1521.0000.119
ActivityDate0.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0510.0000.0970.1191.000

Missing values

2023-01-14T10:33:11.802285image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-01-14T10:33:11.926712image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

IdActivityDateTotalStepsTotalDistanceTrackerDistanceLoggedActivitiesDistanceVeryActiveDistanceModeratelyActiveDistanceLightActiveDistanceSedentaryActiveDistanceVeryActiveMinutesFairlyActiveMinutesLightlyActiveMinutesSedentaryMinutesCalories
015039603664/12/2016131628.508.500.01.880.556.060.025133287281985
115039603664/13/2016107356.976.970.01.570.694.710.021192177761797
215039603664/14/2016104606.746.740.02.440.403.910.0301118112181776
315039603664/15/201697626.286.280.02.141.262.830.029342097261745
415039603664/16/2016126698.168.160.02.710.415.040.036102217731863
515039603664/17/201697056.486.480.03.190.782.510.038201645391728
615039603664/18/2016130198.598.590.03.250.644.710.0421623311491921
715039603664/19/2016155069.889.880.03.531.325.030.050312647752035
815039603664/20/2016105446.686.680.01.960.484.240.028122058181786
915039603664/21/201698196.346.340.01.340.354.650.01982118381775
IdActivityDateTotalStepsTotalDistanceTrackerDistanceLoggedActivitiesDistanceVeryActiveDistanceModeratelyActiveDistanceLightActiveDistanceSedentaryActiveDistanceVeryActiveMinutesFairlyActiveMinutesLightlyActiveMinutesSedentaryMinutesCalories
93088776893915/3/2016108188.2100008.2100000.01.390.106.670.0119322911892817
93188776893915/4/20161819316.29999916.2999990.010.420.315.530.0066821211543477
93288776893915/5/20161405510.67000010.6700000.05.460.824.370.00671518811703052
93388776893915/6/20162172719.34000019.3400000.012.790.296.160.00961723210954015
93488776893915/7/2016123328.1300008.1300000.00.080.966.990.001052827110364142
93588776893915/8/2016106868.1100008.1100000.01.080.206.800.0017424511742847
93688776893915/9/20162022618.25000018.2500000.011.100.806.240.05731921711313710
93788776893915/10/2016107338.1500008.1500000.01.350.466.280.00181122411872832
93888776893915/11/20162142019.55999919.5599990.013.220.415.890.00881221311273832
93988776893915/12/201680646.1200006.1200000.01.820.044.250.002311377701849